Developing an AI Enabled Salutogenic Leadership Model for Abadan Oil Refinery

Sajjad Aalikhani Nasab; Mohammad  Taheri Roozbehani; Hossein  Yarahmadi; Mohammad Reza Jaber Ansari; Hassan  Piryaei

Authors

Sajjad Aalikhani Nasab Department of Management, Bo. C., Islamic Azad University, Borujerd, Iran Author https://orcid.org/0000-0003-1809-2380
Mohammad Taheri Roozbehani Department of Management, Bo. C., Islamic Azad University, Borujerd, Iran Corresponding Author https://orcid.org/0009-0008-8351-0386
Hossein Yarahmadi Department of Computer Engineering, Bo. C., Islamic Azad University, Borujerd, Iran Author https://orcid.org/0000-0002-0722-7596
Mohammad Reza Jaber Ansari Department of Management, Bo. C., Islamic Azad University, Borujerd, Iran Author
Hassan Piryaei Department of Mathematics, Bo. C., Islamic Azad University, Borujerd, Iran Author https://orcid.org/0000-0001-8643-4464

Keywords:

Salutogenic Leadership, Artificial Intelligence, Digital Transformation, Organizational Health, Oil Refining Industry, Abadan Oil Refinery.

Abstract

To develop a context-sensitive model of artificial intelligence (AI) enabled salutogenic leadership for Abadan Oil Refinery, integrating occupational well-being with the organizational requirements of digital transformation. This applied qualitative study integrated theoretical evidence with semi-structured interviews with 18 academic and organizational experts selected purposively for their knowledge of leadership, management, and AI applications. Audio-recorded interviews were transcribed verbatim and analyzed in ATLAS.ti using open, axial, and selective coding. Two independent coders reconciled disagreements through discussion; the reported Cohen’s kappa was 0.79. Preliminary categories were also reviewed by participating experts. The analysis generated 140 initial open codes and a six-category paradigm model. The model comprised causal conditions, intervening conditions, contextual conditions, strategies, a core phenomenon, and anticipated outcomes. Its core combined health-promoting and sustainable leadership, psychological coherence and occupational health, and readiness for human–AI collaboration. Causal conditions concerned leadership relationships, organizational and technological drivers, and attitudes toward technology. Contextual and intervening conditions encompassed health culture, job demands and resources, digital infrastructure, psychological capacities, and digital leadership. Strategies emphasized health support, stress management, leadership development, employee learning, and responsible technological adaptation. Anticipated outcomes concerned employee health and well-being, work attitudes and engagement, and sustainable organizational performance. The model frames AI as a resource for human decision-making within a health-promoting leadership approach. It provides an exploratory framework for refinery management rather than evidence that AI implementation improves health, safety, or productivity. The proposed relationships require prospective evaluation.

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